scholarly journals Use of an Active Canopy Sensor and SPAD Chlorophyll Meter to Quantify Geranium Nitrogen Status

HortScience ◽  
2012 ◽  
Vol 47 (1) ◽  
pp. 45-50 ◽  
Author(s):  
Yun-wen Wang ◽  
Bruce L. Dunn ◽  
Daryl B. Arnall ◽  
Pei-sheng Mao
Keyword(s):  
Green Leaf ◽  
Fertilizer Treatment ◽  
N Content ◽  
Chlorophyll Meter ◽  
N Concentration ◽  
Flower Traits ◽  
Leaf N Content ◽  
N Rates ◽  
N Status ◽  
Leaf N

This research was conducted to investigate the potentials of normalized difference vegetation index (NDVI), a Soil-Plant Analyses Development (SPAD) chlorophyll meter, and leaf nitrogen (N) concentration [% dry matter (DM)] for rapid determination of N status in potted geraniums (Pelargonium ×hortorum). Two F1 cultivars were chosen to represent a dark-green leaf cultivar, Horizon Deep Red, and a light-green leaf cultivar, Horizon Tangerine, and were grown in a soilless culture system. All standard 6-inch (15.24-cm) pots filled with a medium received an initial top-dress application of 5 g controlled-release fertilizer (15N–9P–12K), then plants were supplemented with additional N in the form of urea at 0, 50, 100, or 200 mg·L−1 N every few days to produce plants ranging from N-deficient to N-sufficient. The NDVI readings of individual plants from a NDVI pocket sensor developed by Oklahoma State University were collected weekly until the flowering stage. Data on flower traits, including number of pedicels (NOP), number of full umbels per pot (NOFU), total number of flowers per pot (TNF), number of flowers per pedicel (NOF), and inflorescences diameter (IFD), were collected 3 months after initial fertilizer treatment. After measuring flower traits, pedicels were removed from each pot, and SPAD value, NDVI, and leaf N concentration (g·kg−1 DM) were measured simultaneously. Cultivar and N rate significantly affected all but two flower and one N status parameters studied. The coefficient of determination R2 showed that NOP, NOFU, and TNF traits were more related to the N rates and the status parameters studied for ‘Horizon Tangerine’ than for ‘Horizon Deep Red’. For the latter cultivar, NOP and TNF traits were highly related to NDVI and SPAD values than N rates and leaf N content parameters. Correlation analysis indicated that the NDVI readings (R2 = 0.848 and 0.917) and SPAD values (R2 = 0.861 and 0.950) were significantly related to leaf N content (g·kg−1 DM) between cultivars. However, sensitivity of the NDVI and chlorophyll values to N application rate in geranium was slightly less than leaf N content. Strong correlations (R2 = 0.974 and 0.979, respectively) between NDVI and SPAD values were found within cultivars. The results demonstrated NDVI and SPAD values can be used to estimate N status in geranium. Because the pocket NDVI sensor will be cheaper than the SPAD unit, it has an advantage in determining N content in potted ornamentals.

scholarly journals LEAF TOTAL NITROGEN CONCENTRATION AS AN INDICATOR OF NITROGEN STATUS FOR PLANTLETS AND YOUNG PLANTS OF EUCALYPTUS CLONES

2015 ◽  
Vol 39 (4) ◽  
pp. 1127-1140 ◽  
Author(s):  
Eric Victor de Oliveira Ferreira ◽  
Roberto Ferreira Novais ◽  
Bruna Maximiano Médice ◽  
Nairam Félix de Barros ◽  
Ivo Ribeiro Silva
Keyword(s):  
Total Nitrogen ◽  
Block Design ◽  
Nitrogen Concentration ◽  
Soil N ◽  
Total N ◽  
Chlorophyll Meter ◽  
N Concentration ◽  
Total Nitrogen Concentration ◽  
N Status ◽  
Leaf N

The use of leaf total nitrogen concentration as an indicator for nutritional diagnosis has some limitations. The objective of this study was to determine the reliability of total N concentration as an indicator of N status for eucalyptus clones, and to compare it with alternative indicators. A greenhouse experiment was carried out in a randomized complete block design in a 2 × 6 factorial arrangement with plantlets of two eucalyptus clones (140 days old) and six levels of N in the nutrient solution. In addition, a field experiment was carried out in a completely randomized design in a 2 × 2 × 2 × 3 factorial arrangement, consisting of two seasons, two regions, two young clones (approximately two years old), and three positions of crown leaf sampling. The field areas (regions) had contrasting soil physical and chemical properties, and their soil contents for total N, NH+4-N, and NO−3-N were determined in five soil layers, up to a depth of 1.0 m. We evaluated the following indicators of plant N status in roots and leaves: contents of total N, NH+4-N, NO−3-N, and chlorophyll; N/P ratio; and chlorophyll meter readings on the leaves. Ammonium (root) and NO−3-N (root and leaf) efficiently predicted N requirements for eucalyptus plantlets in the greenhouse. Similarly, leaf N/P, chlorophyll values, and chlorophyll meter readings provided good results in the greenhouse. However, leaf N/P did not reflect the soil N status, and the use of the chlorophyll meter could not be generalized for different genotypes. Leaf total N concentration is not an ideal indicator, but it and the chlorophyll levels best represent the soil N status for young eucalyptus clones under field conditions.

scholarly journals Dissection of hyperspectral reflectance to estimate nitrogen and chlorophyll contents in tea leaves based on machine learning algorithms

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hiroto Yamashita ◽  
Rei Sonobe ◽  
Yuhei Hirono ◽  
Akio Morita ◽  
Takashi Ikka
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Visible Region ◽  
Machine Learning Algorithms ◽  
Hyperspectral Reflectance ◽  
N Content ◽  
Green Leaves ◽  
Leaf N Content ◽  
N Status ◽  
Leaf N

Abstract Nondestructive techniques for estimating nitrogen (N) status are essential tools for optimizing N fertilization input and reducing the environmental impact of agricultural N management, especially in green tea cultivation, which is notably problematic. Previously, hyperspectral indices for chlorophyll (Chl) estimation, namely a green peak and red edge in the visible region, have been identified and used for N estimation because leaf N content closely related to Chl content in green leaves. Herein, datasets of N and Chl contents, and visible and near-infrared hyperspectral reflectance, derived from green leaves under various N nutrient conditions and albino yellow leaves were obtained. A regression model was then constructed using several machine learning algorithms and preprocessing techniques. Machine learning algorithms achieved high-performance models for N and Chl content, ensuring an accuracy threshold of 1.4 or 2.0 based on the ratio of performance to deviation values. Data-based sensitivity analysis through integration of the green and yellow leaves datasets identified clear differences in reflectance to estimate N and Chl contents, especially at 1325–1575 nm, suggesting an N content-specific region. These findings will enable the nondestructive estimation of leaf N content in tea plants and contribute advanced indices for nondestructive tracking of N status in crops.

scholarly journals Spad index for diagnosis of nitrogen status in ‘Esmeralda’ peach

2021 ◽  
Vol 43 (1) ◽  
Author(s):  
Jorge Atílio Benati ◽  
Gilberto Nava ◽  
Newton Alex Mayer
Keyword(s):  
Block Design ◽  
Middle Part ◽  
Full Bloom ◽  
N Content ◽  
Randomized Block Design ◽  
Positive Linear Correlation ◽  
Leaf N Content ◽  
N Rates ◽  
Spad Readings ◽  
Leaf N

Abstract The objective of this research was to evaluate the technical feasibility of SPAD index in the diagnosis of N status in ‘Esmeralda’ peach. The field trial, with five N rates applied to the soil (0, 40, 80, 120 and 160 kg ha-1 of N as urea form) was conducted in a randomized block design with four replications. During the years 2014, 2015, 2016 and 2017, SPAD readings were carried out with a Minolta SPAD-502 chlorophyll meter, in the leaf middle part, in 40 leaves per plot. The leaf N content determination was performed in CHN-S Elemental Analyzer. SPAD index and leaf N content increased in a linear way in response to increasing N rates applied in soil. There was a positive linear correlation between SPAD index and N concentration in leaves (0.652; 0.756; 0.762 and 0.767, p<0.05). SPAD index can be used for nutritional N diagnosis purpose in peach when readings are taken between the 13th and 15th weeks after full bloom. In the range between 39 and 49, the SPAD index indicates the leaf N content is included in “normal” class (33 – 45 g kg-1) of agronomic interpretation for the States of Rio Grande do Sul and Santa Catarina, Brazil.

scholarly journals Field Assessment of Macronutrients and Nitrogen in Apple Leaves Using a Chlorophyll Meter

2019 ◽  
Vol 29 (3) ◽  
pp. 300-307 ◽  
Author(s):  
Youngsuk Lee ◽  
Hun Joong Kweon ◽  
Moo-Yong Park ◽  
Dongyong Lee
Keyword(s):  
Nutrient Status ◽  
Nutrient Content ◽  
N Content ◽  
Chlorophyll Meter ◽  
Content Assessment ◽  
Growing Period ◽  
Leaf Chlorophyll ◽  
Nutrient Profiles ◽  
Leaf N Content ◽  
Leaf N

Nutrient content assessment of plant tissues is widely performed by farmers to determine the appropriate amount of fertilization to use for their crops. A nondestructive leaf chlorophyll meter is one of the most commonly used devices for performing field assessments of the nutrient status of leaves. However, it is challenging to use a chlorophyll meter to assess the nutritional status of perennial plants, such as the apple (Malus ×domestica) tree, because of the difficulty estimating nitrogen (N) during the entire growing period. We compared the chlorophyll meter readings with leaf nutrient profiles collected from young ‘Arisoo’/M.9 apple trees throughout the growing period. A significant positive correlation between the chlorophyll meter readings and leaf N content was found from May to August during the midseason. Regression analysis indicated that the best sampling time for predicting the foliar N content of apple tress is from late June to late July. This result suggests that a reliable leaf N assessment can be performed in a rapid, nondestructive way in apple orchards.

scholarly journals 504 Urea Uptake and Nitrogen Mobilization by Apple Leaves in Relation to Tree Nitrogen Status in the Fall

HortScience ◽  
2000 ◽  
Vol 35 (3) ◽  
pp. 481D-481
Author(s):  
Lailiang Cheng ◽  
Shufu Dong ◽  
Leslie H. Fuchigami
Keyword(s):  
Leaf Area ◽  
N Uptake ◽  
Urea Solution ◽  
N Content ◽  
Wide Range ◽  
Leaf N Content ◽  
N Status ◽  
Foliar Urea ◽  
Whole Tree ◽  
Leaf N

Bench-grafted Fuji/M26 trees were fertigated with seven nitrogen concentrations (0, 2.5, 5.0, 7.5, 10, 15, and 20 mm) by using a modified Hoagland solution from 30 June to 1 Sept. In Mid-October, plants in each N treatment were divided into three groups. One group was destructively sampled to determine background tree N status before foliar urea application. The second group was painted with 3% 15N-urea solution twice at weekly interval on both sides of all leaves while the third group was left as controls. All the fallen leaves from both the 15N-treated and control trees were collected during the leaf senescence process and the trees were harvested after natural leaf fall. Nitrogen fertigation resulted in a wide range of tree N status in the fall. The percentage of whole tree N partitioned into the foliage in the fall increased linearly with increasing leaf N content up to 2.2 g·m–2, reaching a plateau of 50% to 55% with further rise in leaf N. 15N uptake and mobilization per unit leaf area and the percentage of 15N mobilized from leaves decreased with increasing leaf N content. Of the 15N mobilized back to the tree, the percentage of 15N partitioned into the root system decreased with increasing tree N status. Foliar 15N-urea application reduced the mobilization of existing N in the leaves regardless of leaf N status. More 15N was mobilized on a leaf area basis than that from existing N in the leaves with the low N trees showing the largest difference. On a whole-tree basis, the increase in the amount of reserve N caused by foliar urea treatment was similar. We conclude that low N trees are more effective in utilizing N from foliar urea than high N trees in the fall.

scholarly journals Nitrogen requirement and critical N content of stevia grown in two contrasting soils of Bangladesh

2016 ◽  
Vol 3 (1) ◽  
pp. 87-97 ◽  
Author(s):  
Md Maniruzzaman ◽  
Md Akhter Hossain Chowdhury ◽  
KM Mohiuddin ◽  
Tanzin Chowdhury
Keyword(s):  
Plant Height ◽  
Acid Soil ◽  
Calcareous Soils ◽  
Dry Weight ◽  
Leaf Biomass ◽  
N Content ◽  
N Concentration ◽  
Plant Sampling ◽  
Leaf N Content ◽  
N Rates

Nitrogen is recognized as one of the most limiting nutrient for crop growth in Bangladesh and can be supplemented with inorganic fertilizers like urea. The experiment was conducted in the net house of the Department of Agricultural Chemistry, Bangladesh Agricultural University during March to July 2012. The objective was to examine the effects of different levels of N on the growth, leaf biomass yield, N content and to estimate minimum N requirement and critical N content of stevia. The treatments included six N rates (0, 100, 150, 200, 250 and 300 kg ha-1). Plant sampling was done at 15, 30, 45 and 60 days after planting (DAP) to measure plant height, number of branches and leaves, fresh and dry weight of leaves, leaf area and N concentration. The results revealed that all the characters were significantly affected by different N rates. The highest values of all parameters except plant height and N concentration were obtained from 250 kg N ha-1 and the lowest values from N control. Nitrogen application at all levels increased leaf dry yield at harvest by 99 to 505% in acid soil and 69 to 438% in non-calcareous soil, respectively over control. The growth of most parameters was rapid at the later stages (30 to 60 DAP). Leaf N content proportionately increased with the increasing rates of N. The highest N concentration was obtained from its highest application (300 kg N ha-1). The minimum amount of N for maximum leaf biomass production in the plants grown in acid and non-calcareous soils was estimated to be ca 273 and 257 kg ha-1, respectively. The critical N concentration to achieve 80% of the maximum production of stevia leaf was also estimated to be ca 1.43 and 1.50% in the leaves of stevia plants grown in acid and non-calcareous soils, respectivelyRes. Agric., Livest. Fish.3(1): 87-97, April 2016

scholarly journals Effect of Cultivar on Chlorophyll Meter and Canopy Reflectance Measurements in Cucumber

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 509 ◽  
Author(s):  
Romina de Souza ◽  
Rafael Grasso ◽  
M. Teresa Peña-Fleitas ◽  
Marisa Gallardo ◽  
Rodney B. Thompson ◽  
...  
Keyword(s):  
Optical Sensors ◽  
Optical Sensor ◽  
Chlorophyll Concentration ◽  
Vegetation Indices ◽  
Canopy Reflectance ◽  
Cucumis Sativus L ◽  
N Content ◽  
Chlorophyll Meter ◽  
Leaf N Content ◽  
Leaf N

Optical sensors can be used to assess crop N status to assist with N fertilizer management. Differences between cultivars may affect optical sensor measurement. Cultivar effects on measurements made with the SPAD-502 (Soil Plant Analysis Development) meter and the MC-100 (Chlorophyll Concentration Meter), and of several vegetation indices measured with the Crop Circle ACS470 canopy reflectance sensor, were assessed. A cucumber (Cucumis sativus L.) crop was grown in a greenhouse, with three cultivars. Each cultivar received three N treatments, of increasing N concentration, being deficient (N1), sufficient (N2) and excessive (N3). There were significant differences between cultivars in the measurements made with both chlorophyll meters, particularly when N supply was sufficient and excessive (N2 and N3 treatments, respectively). There were no consistent differences between cultivars in vegetation indices. Optical sensor measurements were strongly linearly related to leaf N content in each of the three cultivars. The lack of a consistent effect of cultivar on the relationship with leaf N content suggests that a unique equation to estimate leaf N content from vegetation indices can be applied to all three cultivars. Results of chlorophyll meter measurements suggest that care should be taken when using sufficiency values, determined for a particular cultivar

scholarly journals Management of Nitrogen and Irrigation in Lettuce Transplant Production affects Transplant Root and Shoot Development and Subsequent Crop Yields

HortScience ◽  
2005 ◽  
Vol 40 (3) ◽  
pp. 607-610 ◽  
Author(s):  
Puffy Soundy ◽  
Daniel J. Cantliffe ◽  
George J. Hochmuth ◽  
Peter J. Stoffella
Keyword(s):  
Crop Yields ◽  
Irrigation System ◽  
Weight Percent ◽  
Irrigation Frequency ◽  
N Content ◽  
Greenhouse Experiments ◽  
N Concentration ◽  
Shoot Weight ◽  
Leaf N Content ◽  
Leaf N

Lettuce (Lactuca sativa L.) `South Bay' transplant growth and development were evaluated at 0, 30, 60, 90, and 120 mg·L–1 N fertigated at frequencies of every 1, 2, 3, or 4 days in a floatation production system to produce plants with optimum roots and shoots which easily pull from trays. Greenhouse experiments (four) were conducted to evaluate root and shoot weight, percent transplant pulling success, and leaf N content, 28 days after sowing (DAS). Field trials, using transplants produced in Greenhouse experiments 2 and 4, were conducted to evaluated subsequent yield, head quality characteristics, and leaf N content. Generally, as N concentrations increased, dry shoot weight and leaf N concentration increased, and root:shoot ratios decreased linearly or quadratically. Lettuce transplants grown in a floatation irrigation system fertigated every second to third day with 60 to 90 mg·L–1 N resulted in transplants with optimum root systems to achieve the highest pulling success rate from flats. Subsequent yields and head quality were optimum for pretransplant production fertigation N concentration of 60 to 90 mg·L–1, regardless of irrigation frequency.

scholarly journals Nitrogen Requirements of Fresh-market Tomatoes on Hairy Vetch and Black Polyethylene Mulch

HortScience ◽  
1997 ◽  
Vol 32 (2) ◽  
pp. 217-221 ◽  
Author(s):  
Aref A. Abdul-Baki ◽  
John R. Teasdale ◽  
Ronald F. Korcak
Keyword(s):  
Above Ground Biomass ◽  
Fertilizer N ◽  
Hairy Vetch ◽  
Fresh Market ◽  
N Content ◽  
Ground Biomass ◽  
Leaf N Content ◽  
N Rates ◽  
Polyethylene Mulch ◽  
Leaf N

A 3-year experiment was conducted to determine the optimum fertilizer N requirements of fresh-market tomato (Lycopersicon esculentum Mill.) `Sunbeam' grown on a hairy vetch (Vicia villosa Roth.) or black polyethylene mulch. In 1993 and 1994, four rates of fertilizer N (0, 56, 112, and 168 kg·ha-1) as water-soluble NH4NO3 were applied in 14 equal applications through the trickle irrigation system starting 1 week after planting. Four additional rates (224, 280, 336, and 392 kg·ha-1) were applied in 1995 to assess the plant response to supra-optimal levels of N. Hairy vetch produced 3.3–4.5 t·ha-1 of above-ground biomass and a total N content of 126–169 kg·ha-1 in the above-ground biomass. Leaf N content at 7 weeks after transplanting of tomatoes correlated positively with yield from black polyethylene but did not correlate with yield from the hairy vetch plots where leaf N content was optimal at all N rates. Predicted tomato yields were higher for the hairy vetch than for the black polyethylene treatment at all applied N rates in all years. Tomatoes grown in black polyethylene required N at 130 to 144 kg·ha-1 to achieve yields equivalent to those grown following unfertilized hairy vetch. Tomato yield increased in response to applied N in both mulches in all 3 years; optimum N rates of 89 and 190 kg·ha-1 in hairy vetch and black polyethylene, respectively, were predicted by a linear plateau model, and 124 and 295 kg·ha-1 by a quadratic plateau model. The linear plateau model is recommended because it would allow less N to become available for runoff and leaching.

scholarly journals A novel approach for nitrogen diagnosis of wheat canopies digital images by mobile phones based on histogram

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Qi ◽  
Yanan Zhao ◽  
Yufang Huang ◽  
Yang Wang ◽  
Wei Qin ◽  
...  
Keyword(s):  
Neural Network ◽  
Mobile Phones ◽  
Mean Value ◽  
Wheat Cultivars ◽  
N Content ◽  
Color Parameters ◽  
The Neural Network ◽  
The Mean ◽  
Leaf N Content ◽  
Leaf N

AbstractThe accurate and nondestructive assessment of leaf nitrogen (N) is very important for N management in winter wheat fields. Mobile phones are now being used as an additional N diagnostic tool. To overcome the drawbacks of traditional digital camera diagnostic methods, a histogram-based method was proposed and compared with the traditional methods. Here, the field N level of six different wheat cultivars was assessed to obtain canopy images, leaf N content, and yield. The stability and accuracy of the index histogram and index mean value of the canopy images in different wheat cultivars were compared based on their correlation with leaf N and yield, following which the best diagnosis and prediction model was selected using the neural network model. The results showed that N application significantly affected the leaf N content and yield of wheat, as well as the hue of the canopy images and plant coverage. Compared with the mean value of the canopy image color parameters, the histogram could reflect both the crop coverage and the overall color information. The histogram thus had a high linear correlation with leaf N content and yield and a relatively stable correlation across different growth stages. Peak b of the histogram changed with the increase in leaf N content during the reviving stage of wheat. The histogram of the canopy image color parameters had a good correlation with leaf N content and yield. Through the neural network training and estimation model, the root mean square error (RMSE) and the mean absolute percentage error (MAPE) of the estimated and measured values of leaf N content and yield were smaller for the index histogram (0.465, 9.65%, and 465.12, 5.5% respectively) than the index mean value of the canopy images (0.526, 12.53% and 593.52, 7.83% respectively), suggesting a good fit for the index histogram image color and robustness in estimating N content and yield. Hence, the use of the histogram model with a smartphone has great potential application in N diagnosis and prediction for wheat and other cereal crops.

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